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  • Author: Örs Darabont x
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This paper presents an evaluation of different methods used to deliver virtual machines capable of being accessed remotely by thin-clients. The objective of the research was to provide a recommendation for building a cost-effective computer infrastructure for use in two scenarios: as a programming lab, and as an office infrastructure.

We have found that different thin-client solutions based on single board computers are reliable solutions for commercially available thin client replacement, because they can run free Linux-based operating systems, can handle Remote Desktop Protocol, have lower acquisition costs, lower power consumption and offer almost the same computing performance.

For providing remote desktops, there are several methods and virtualization platforms available. We benchmarked some of these platforms in order to choose the one best-suited for implementation. Our conclusion is that Microsoft Remote Desktop Services outperforms the virtualization based solutions, but it entails high license fees. Of the virtualization solutions tested, the VMW are ESXi based one is the most reliable choice.


The fast spread of computer networks and broadband Internet access, and also the development of different operating systems, makes possible to use different virtualization techniques and virtual machines. The release and spread of virtualization platforms makes possible the development of cost-effective information systems that can provide in addition dynamic resource management and simplified system administration.

In this paper we present a comparative performance analysis of Remote Desktop Virtualization based on Hyper-V versus Remote Desktop Services. We introduce system architecture for the two tested scenario and test environment including detailed hardware description.

The main conclusions of the paper are that despite the higher acquisition and maintenance costs, the Remote Desktop Services outperforms the Hyper-V based Remote Desktop Virtualization in memory, CPU and also storage management.